Many studies have explored how individual differences can affect users' susceptibility to cybersickness in a VR application. However, the lack of strategy to integrate the influence of each factor on cybersickness makes it difficult to utilize the results of existing research. Based on the fuzzy logic theory that can represent the effect of different factors as a single value containing integrated information, we developed two approaches including the knowledge-based Mamdani-type fuzzy inference system and the data-driven Adaptive neuro-fuzzy inference system (ANFIS) to involve three individual differences (Age, Gaming experience and Ethnicity). We correlated the corresponding outputs with the simulator sickness questionnaire (SSQ) scores in a simple navigation scenario. The correlation coefficients obtained through a 4- fold cross validation were found statistically significant with both fuzzy logic approaches, indicating their effectiveness to influence the occurrence and the level of cybersickness. Our work provides insights to establish customized experiences for VR navigation by involving individual differences.

As part of an evaluation process of user experience realism in a Virtual Reality (VR) system, we focus in this paper on one of the core characteristics of vision: the relationship between contrast and luminance. The experiment aims at validating in VR reaction time predictions given by Rea and Ouellette's model. The subjects have to distinguish, as fast as they can, a target object from an uniform background. Our results did not match the predictions of the model. Our subjects showed higher performance in performing the task than expected. At low level of contrast, our subjects could easily perceive a target they should not have been able to see at all. This is explained by the size of the visual field surrounding the target: at low level of visibility, the larger the surrounding, the easier perception the is. We conclude that the Rea and Ouellette's model could be applied in VR if a specific visual field size factor was added.

Studies using virtual reality environments (VE) have shown that subjects can perform path integration tasks with acceptable performance. However, in these studies, subjects could walk naturally across large tracking areas, or researchers provided them with large- immersive displays. Unfortunately, these configurations are far from current consumer-oriented VEs (COVEs), and little is known about how their limitations influence this task. Using a triangle completion paradigm, we assessed the subjects' spatial performance when developing path integration tasks in two consumer-oriented displays (an HTC Vive and a GearVR) and two consumer-oriented interaction devices (a Virtuix Omni motion platform and a Touchpad Control). Our results show that when locomotion is available (motion platform condition), there exist significant effects regarding the display and the path. In contrast, when locomotion is mediated no effect was found. Some future research directions are therefore proposed.

Homing is a fundamental task which plays a vital role in spatial navigation. Its performance depends on the computation of a homing vector, where human beings can use simultaneously two different cognitive strategies: an online strategy based on the self-motion cues known as path integration (PI), and an offline strategy called piloting based on the spatial image of the path. Studies using virtual reality environments (VE) have shown that human being can perform homing tasks with acceptable performance. However, in these studies, subjects were able to walk naturally across large tracking areas, or researchers provided them with high-end large-immersive displays. Unfortunately, these configurations are far from current consumer-oriented devices, and very little is known about how their limitations can influence these cognitive processes. Using a triangle completion paradigm, we assessed homing tasks in two consumer-oriented displays (an HTC Vive and a GearVR) and two consumer-oriented interaction devices (a Virtuix Omni Treadmill and a Touchpad Control). Our results show that when locomotion is available (treadmill condition), there exist significant effects regarding display and path complexity. In contrast, when locomotion is restricted (touchpad condition), some effects on path complexity were found. Thus, some future research directions are therefore proposed.

Building Information Modelling (BIM) is an up-and-coming methodology and technology used in the Architecture, Engineering and Construction (AEC) industry, that allows data centralization and stakeholders' collaboration. But to check the accuracy of the work done on the worksite, it is necessary first to go on site and then to modify the BIM model. This paper presents a mixed reality (MR) application based on BIM data and drone videos, allowing off-site construction supervision. It permits to make annotations about differences between what has been planned in BIM and what has been built, using superimposition of the two sources. Then these ones can be transferred to the BIM model for corrections. Finally, we evaluate our work with building construction experts, providing to them a questionnaire to grade the application and to get feedback. Our major result is that as for them the application does really help to do construction supervisions; however, they suggest that the application should provide more interactions with the 3D model and with the videos.

Current virtual environments (VE) enable perceiving haptic stimuli to facilitate 3D user interaction, but lack brain-interfacial contents. Using electroencephalography (EEG), we undertook a feasibility study on exploring event-related potential (ERP) patterns of the user's brain responses during haptic interaction within a VE. The interaction was flying a virtual drone along a curved transmission line to detect defects under the stimuli (e.g., force increase and/or vibrotactile cues). We found that there were variations in the peak amplitudes and latencies (as ERP patterns) of the responses at about 200 ms post the onset of the stimuli. The largest negative peak occurred during 200~400 ms after the onset in all vibration-related blocks. Moreover, the amplitudes and latencies of the peak were differentiable among the vibration-related blocks. These findings imply feasible decoding of the brain responses during haptic interaction within VEs.

Travel in a real environment is a common task that human beings conduct easily and subconsciously. However transposing this task in virtual environments (VEs) remains challenging due to input devices and techniques. Considering the well-described sensory conflict theory, we present a semiautomatic travel method based on path planning algorithms and gaze-directed control, aiming at reducing the generation of conflicted signals that may confuse the central nervous system. Since gaze-directed control is user-centered and path planning is goal-oriented, our semiautomatic technique makes up for the deficiencies of each with smoother and less jerky trajectories.

This paper proposes a new objective metric of visually induced motion sickness (VIMS) in the context of navigation in virtual environments (VEs). Similar to motion sickness in physical environments, VIMS can induce many physiological symptoms such as general discomfort, nausea, disorientation, vomiting, dizziness and fatigue. To improve user satisfaction with VR applications, it is of great significance to develop objective metrics for VIMS that can analyze and estimate the level of VR sickness when a user is exposed to VEs. One of the well-known objective metrics is the postural instability. In this paper, we trained a LSTM model for each participant using a normal-state postural signal captured before the exposure, and if the postural sway signal from post-exposure was sufficiently different from the pre-exposure signal, the model would fail at encoding and decoding the signal properly; the jump in the reconstruction error was called loss and was proposed as the proposed objective measure of simulator sickness. The effectiveness of the proposed metric was analyzed and compared with subjective assessment methods based on the simulator sickness questionnaire (SSQ) in a VR environment, achieving a Pearson correlation coefficient of. 89. Finally, we showed that the proposed method had the potential to be deployed within a closed-loop system and get real-time performance to predict VR sickness, opening new insights to develop user-centered and customized VR applications based on physiological feedback.

International audience

In a three-dimensional (3D) virtual environment (VE), proper collaboration between vibrotactile and force cues - two cues of the haptic modality - is important to facilitate task performance of human users. Many studies report that collaborations between multi-sensory cues follow maximum likelihood estimation (MLE). However, an existing work finds that MLE yields a mean and an amplitude mismatches when interpreting the collaboration between the vibrotactile and force cues. We thus proposed mean-shifted MLE and conducted a human study to investigate the mismatches. For the study, we created a VE to replicate the visual scene, the 3D interactive task, and the cues from the existing work. Our participants were biased to rely on the vibrotactile cue for their tasks, departing from unbiased reliance on both cues in the existing work. Assessments of task completion time and task accuracy validated the replication. We found that based on task accuracy MLE explained the cue collaboration to certain degrees, agreed with the existing work. Mean-shifted MLE remedied the mean mismatch, but maintained the amplitude mismatch. Further examinations revealed that the collaboration between both cues may not be entirely additive. This sheds an insight for proper modeling of the collaboration between the vibrotactile and force cues to aid interactive tasks in VEs.

This poster formulates the concept of heterogeneous distributed mixed reality (HDMR) applications in order to state some interesting research questions in this domain. HDMR applications give synchronous access to shared virtual worlds, from diverse mixed reality (MR) hardware, and at similar levels of functionality. We show the relationship between HDMR and previous concepts, state challenges in their development, and illustrate this concept and its challenges with an example.

We propose an innovative method to navigate in a virtual environment by adapting the acceleration parameters to users in real time, in order to reduce cybersickness. Indeed, navigation parameters for most navigation interfaces are still determined by rate-control devices. Inappropriate parameter settings may lead to strong sickness, making the application unusable. Past research found that especially accelerations should not be set too high. Here, we define the accelerations as a function of a cybersickness indicator: the Electro-Dermal Activity (EDA). A pre-study was conducted to test the effectiveness of our approach and showed promising results where cybersickness tends to decrease with our adaptive navigation method.

Nowadays, virtual reality (VR) is widely used in the AEC (architecture, engineering and construction) industry. One crucial issue is how to reuse Building Information Modeling (BIM) models in VR applications. This paper presents an approach for a smart adaptation of BIM models for using in VR scene, by following the needs expressed by building projects actors. The main adaptation consists in filtering BIM data to keep the necessary ones for VR, according to the user objectives. Moreover, VR system should be chosen by taking into account the purpose of usage of the VR model. This approach is applied to a study case of a nursery building project.

Vibrotactile and force cues of the haptic modality is increasing used to facilitate interactive tasks in three-dimensional (3D) virtual environments (VE). While maximum likelihood estimation (MLE) explains the integration of multi-sensory cues in many studies, an existing work yielded mean and amplitude mismatches when using MLE to interpret the integration of vibrotactile and force cues. To investigate these mismatches, we proposed mean-shifted MLE and conducted a study of comparing MLE and mean-shift MLE. Mean-shifted MLE shared the same additive assumption of the cues as MLE, but took account mean differences of both cues. In a VE, the study replicated the visual scene, the 3D interactive task, and the cues from the existing work. All human participants in the study were biased to rely on the vibrotactile cue for their task, departing from unbiased reliance towards both cues in the existing work. After validating the replications, we applied MLE and mean-shifted MLE to interpret the integration of the vibrotactile and force cues. Similar to the existing work, MLE failed to explain the mean mismatch. Mean-shifted MLE remedied this mismatch, but maintained the amplitude mismatch. Further examinations revealed that the integration of the vibrotactile and force cues might violate the additive assumption of MLE and mean-shifted MLE. This sheds a light for modeling the integration of vibrotactile and force cues to aid 3D interactive tasks within VEs.

Proper integration of sensory cues facilitates 3D user interaction within virtual environments (VEs). Studies showed that the integration of visual and haptic cues follows maximum likelihood estimation (MLE). Little effort focuses however on the mechanism of integrating force and vibrotactile cues. We thus investigated MLE's suitability for integrating these cues. Within a VE, human users undertook 3D interaction of navigating a flying drone along a high-voltage transmission line for inspection. The users received individual force or vibrotactile cues, and their combinations in collocated and dislocated settings. The users' task performance including completion time and accuracy was assessed under each individual cue and setting. The presence of the vibrotactile cue promoted a better performance than the force cue alone. This agreed with the applicability of tactile cues for sensing 3D surfaces, herein setting a baseline for using MLE. The task performance under the collocated setting indicated a degree of combining the individual cues. In contrast, the performance under the dislocated setting was alike under the individual vibrotactile cue. These observations imply a possible role of MLE in integrating force and vibrotactile cues for 3D user interaction within VEs.

In co-located collaborative environment for product design, new groupware of multi-view system allows multiple experts to have individual visual information. A co-located multi-view VR system and a multidisciplinary task have been created and studied. Results show that using multi-view VR system achieves a better effectiveness and user performance. Then, an application for collaborative ergonomic design is explored and an industrial multidisciplinary scenario is realized with proposed system.

Navigation in a 3D immersive virtual environment is known to be prone to visually induced motion sickness (VIMS). Several psychophysiological and behavioral methods have been used to measure the level of sickness of a user, among which is postural instability. This study investigates all the features that can be extracted from the body postural sway: area of the projection of the center of gravity (mainly considered in past studies) and its shape and the frequency components of the signal’s spectrum, in order to estimate and predict the occurrence of sickness in a typical virtual reality (VR) application.After modeling and simulation of the body postural sway, an experiment on 17 subjects identified a relation between the level of sickness and the variation both in the time and frequency domains of the body sway signal. The results support and go further into detail of findings of past studies using postural instability as an efficient indicator of sickness, giving insight to better monitor VIMS in a VR application.

We present a system, intended for automotive design review use cases, that incorporates a tracked tablet in a CAVE, where both the tablet and the CAVE provide different views and interaction possibilities within the same virtual scene. At its core, this idea is not novel. However, the literature reveals few examples of this paradigm in which virtual information is presented on a second physical device to augment an immersive virtual environment. Similarly, it is unclear where the system should be positioned within existing augmented/mixed/virtual reality taxonomies. We argue that interactions occur within a nesting of virtual and physical contexts, and that formalizing these relationships is important when attempting to understand perceptual issues. The goal of this paper is, thus, to describe the new system by proposing a scheme to formally identify sources of bias and then adapting an existing taxonomy to classify such systems.

Selection of moving targets is a common, yet complex task in human-computer interaction (HCI) and virtual reality (VR). Predicting user intention may be beneficial to address the challenges inherent in interaction techniques for moving-target selection. This article extends previous models by integrating relative head-target and hand-target features to predict intended moving targets. The features are calculated in a time window ending at roughly two-thirds of the total target selection time and evaluated using decision trees. With two targets, this model is able to predict user choice with up to ~ 72% accuracy on general moving-target selection tasks and up to ~ 78% by also including task-related target properties.

This article proposes a method based on wavelet transform and neural networks for relating pupillary behavior to psychological stress. The proposed method was tested by recording pupil diameter and electrodermal activity during a simulated driving task. Self-report measures were also collected. Participants performed a baseline run with the driving task only, followed by three stress runs where they were required to perform the driving task along with sound alerts, the presence of two human evaluators, and both. Self-reports and pupil diameter successfully indexed stress manipulation, and significant correlations were found between these measures. However, electrodermal activity did not vary accordingly. After training, the four-way parallel neural network classifier could guess whether a given unknown pupil diameter signal came from one of the four experimental trials with 79.2% precision. The present study shows that pupil diameter signal has good discriminating power for stress detection.

This paper proposes a navigation technique for traveling inside a real-scale 3D model based on human gesture analysis. In the first step, a simple threshold is used as a criterion to analyze gestures. In the next step, a complex criterion will be imposed to the analysis to improve the navigation technique. Walking is a periodic signal and moving feet up and down is a part which is repeated. A mother wavelet is allocated to the selected pattern. Then the position of the pattern is recognized by applying Multi Resolution Analysis (MRAs). The movement command is generated and sent to the graphic render (as a movement command). Analytical results show a very high precision performance in the presence of noise, scale variation and superposition of other signals. Practical experiments also verify the same promising results.

The paper presents a new mother wavelet adapted from a specific pattern. Wavelet multi-resolution analysis uses this wavelet to detect the position of the pattern in an Infra-Red (IR) signal under scale variation and the presence of noise. IR signal is extracted from IR image sequence recorded by an IR camera, Time of Flight (TOF) sensor configuration. The maximum correlation between the pattern and the signal of interest will be used as a criterion to define the mother wavelet. The proposed mother wavelet were tested and verified under the scale variation and the presence of noise. The experimental tests and performance analysis show promising results for both scale variation and noisy signal. 90% accuracy for the proposed wavelet under intensive noisy condition (50% of the signal amplitude) is guaranteed and high precision is expected under real condition.

Aircraft cockpits are advanced interfaces dedicated to the interaction and exchange of observations and commands between the pilot and the flying system. The design process of cockpits is benefiting from the use of Virtual Reality technologies: early ergonomics and layout analysis through the exploration of numerous alternatives, availability all along the cockpit life cycle of a virtual product ready for experimentation, reduced usage of costly physical mock-ups. Nevertheless, the construction of a virtual cockpit with the adequate performances is very complex. Due to the fact that the CAD based digital mock-up used for setting up the virtual cockpit is very large, one challenge is to achieve interactivity while maintaining the quality of rendering. The reduction of the information contained in the CAD database shall achieve a sufficient frame rate without degradation of the geometrical visual quality of the virtual cockpit which would alleviate the relevance of ergonomics and layout studies. This paper proposes to control the simplification process by using objective criteria based on considerations about the cockpit application and the visual performances of human beings. First, it presents the results of studies on the characteristics of the Human Visual System linked to virtual reality and visualization applications. Illustrated by first results, it establishes how to control simplifications in a rational and automatic way.